nodes/BobRandomNumber-ComfyUI-BasicOllama
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BobRandomNumber
2025-11-30 17:16:07 -05:00
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parent 21ecd4a3fd
commit 20af800bb8
3 changed files with 98 additions and 60 deletions
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BasicOllama.py
+51 -32
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@@ -60,12 +60,21 @@ def get_ollama_url():
with open(config_path, 'r') as f:
config = json.load(f)
ollama_url = config.get("OLLAMA_URL", "http://localhost:11434")
except:
print("Error: Ollama URL not found, using default")
except FileNotFoundError:
print("Error: config.json not found, using default Ollama URL.")
ollama_url = "http://localhost:11434"
except json.JSONDecodeError:
print("Error: Could not decode config.json, using default Ollama URL.")
ollama_url = "http://localhost:11434"
except Exception as e:
print(f"An unexpected error occurred: {e}, using default Ollama URL.")
ollama_url = "http://localhost:11434"
return ollama_url
class BasicOllama:
_connection_error_printed = False
_success_message_printed = False
def __init__(self):
self.ollama_url = get_ollama_url()
@@ -74,13 +83,21 @@ class BasicOllama:
ollama_url = get_ollama_url()
try:
response = requests.get(f"{ollama_url}/api/tags")
if response.status_code == 200:
models = response.json().get('models', [])
return [model['name'] for model in models]
return ["llama2"]
except Exception as e:
print(f"Error fetching Ollama models: {str(e)}")
return ["llama2"]
response.raise_for_status()
models = response.json().get('models', [])
if not cls._success_message_printed:
print("Ollama available.")
cls._success_message_printed = True
cls._connection_error_printed = False # Reset on success
return [model['name'] for model in models]
except requests.exceptions.RequestException:
cls._success_message_printed = False # Reset on failure
if not cls._connection_error_printed:
print("Failed connection to Ollama.")
cls._connection_error_printed = True
return []
@classmethod
def INPUT_TYPES(cls):
@@ -92,7 +109,6 @@ class BasicOllama:
return {
"required": {
"prompt": ("STRING", {"default": "", "multiline": True}),
"input_type": ([ "text", "image"], {"default": "text"}),
"ollama_model": (cls.get_ollama_models(),),
"keep_alive": ("INT", {"default": 0, "min": 0, "max": 60, "step": 1}),
"saved_sys_prompt": (prompt_structures,),
@@ -113,14 +129,17 @@ class BasicOllama:
FUNCTION = "generate_content"
CATEGORY = "Ollama"
def generate_content(self, prompt, input_type, ollama_model, keep_alive, use_sys_prompt_below, saved_sys_prompt, system_prompt, image1=None, image2=None, image3=None, image4=None, image5=None):
def generate_content(self, prompt, ollama_model, keep_alive, use_sys_prompt_below, saved_sys_prompt, system_prompt, image1=None, image2=None, image3=None, image4=None, image5=None):
if not ollama_model:
return ("Ollama models not found. Is Ollama running?",)
url = f"{self.ollama_url}/api/generate"
system_prompt_content = ""
if use_sys_prompt_below:
system_prompt_content = system_prompt
print("Applying user provided system prompt")
else:
# Dynamically load templates and apply the selected one
prompt_templates = get_prompt_files()
if saved_sys_prompt in prompt_templates:
system_prompt_content = prompt_templates[saved_sys_prompt]
@@ -128,32 +147,23 @@ class BasicOllama:
payload = {
"model": ollama_model,
"prompt": prompt,
"stream": False,
"keep_alive": f"{keep_alive}m",
}
if system_prompt_content:
payload["system"] = system_prompt_content
payload.update({
"prompt": prompt,
"stream": False,
"keep_alive": f"{keep_alive}m"
})
all_images = [image1, image2, image3, image4, image5]
provided_images = [img for img in all_images if img is not None]
if provided_images:
print(f"Processing {len(provided_images)} image(s) for Ollama API")
image_data = [tensor_to_base64(img) for img in provided_images]
payload["images"] = image_data
try:
if input_type == "image":
all_images = [image1, image2, image3, image4, image5]
provided_images = [img for img in all_images if img is not None]
if provided_images:
print(f"Processing {len(provided_images)} image(s) for Ollama API")
image_data = []
for img in provided_images:
base64_image = tensor_to_base64(img)
image_data.append(base64_image)
payload["images"] = image_data
payload["prompt"] = f"Analyze these image(s): {prompt}"
response = requests.post(url, json=payload)
response.raise_for_status()
@@ -182,8 +192,17 @@ class BasicOllama:
textoutput = clean_text
return (textoutput,)
except requests.exceptions.RequestException as e:
error_message = f"API Error: {e}"
if e.response:
error_message += f"\nStatus Code: {e.response.status_code}"
try:
error_message += f"\nResponse: {e.response.json()}"
except json.JSONDecodeError:
error_message += f"\nResponse: {e.response.text}"
return (error_message,)
except Exception as e:
return (f"API Error: {str(e)}",)
return (f"An unexpected error occurred: {e}",)
NODE_CLASS_MAPPINGS = {
"BasicOllama": BasicOllama,
README.md
+47 -28
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@@ -6,51 +6,52 @@ A simplified node that provides access to Ollama. It allows you to send prompts,
**You must have Ollama installed and running on your local machine for this node to function.** You can download it from [https://ollama.com/](https://ollama.com/).
![](https://github.com/BobRandomNumber/ComfyUI-BasicOllama/blob/main/BasicOllama.png)
!\[](https://github.com/BobRandomNumber/ComfyUI-BasicOllama/blob/main/BasicOllama.jpg)
## 🚀 Features
* **Direct Ollama Integration:** Seamlessly connect to your local Ollama instance.
* **System Prompt Support:** Utilize the `system` parameter in the Ollama API for more control over model behavior.
* **Dynamic Prompt Templates:** Load system prompts from `.txt` files in the `prompts` directory.
* **Text and Image Support:** Send both text prompts and images to multimodal Ollama models.
* **Multiple Image Inputs:** Input up to five images for analysis.
* **Easy Configuration:** Quickly set up your Ollama URL via a `config.json` file.
* **Direct Ollama Integration:** Seamlessly connect to your local Ollama instance.
* **Automatic Image Detection:** The node automatically detects if an image is connected and sends it to Ollama for multimodal analysis, simplifying the workflow.
* **System Prompt Support:** Utilize the `system` parameter in the Ollama API for more control over model behavior.
* **Dynamic Prompt Templates:** Easily load your own system prompts from `.txt` files in the `prompts` directory.
* **Multiple Image Inputs:** Input up to five images for analysis.
* **Easy Configuration:** Quickly set up your Ollama URL via a `config.json` file.
## 📦 Installation
1. **Clone the Repository:**
Navigate to your `ComfyUI/custom_nodes` directory and clone this repository:
```bash
1. **Clone the Repository:**
Navigate to your `ComfyUI/custom\_nodes` directory and clone this repository:
  ```bash
git clone https://github.com/BobRandomNumber/ComfyUI-BasicOllama
```
2. **Install Dependencies:**
Navigate to the newly cloned directory and install the required packages:
```bash
2. **Install Dependencies:**
Navigate to the newly cloned directory and install the required packages:
  ```bash
cd ComfyUI-BasicOllama
pip install -r requirements.txt
```
3. **Restart ComfyUI:**
Restart your ComfyUI instance to load the new custom node.
3. **Restart ComfyUI:**
Restart your ComfyUI instance to load the new custom node.
## ✨ Usage
The `BasicOllama` node can be found under the `Ollama` category in the ComfyUI menu.
The `BasicOllama` node can be found under the `Ollama` category in the ComfyUI menu. Simply connect an image to one of the `image` inputs to have it automatically included in your prompt.
### Inputs
| Name | Type | Description |
| ---------------------- | ---------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt` | `STRING` | The main text prompt to send to the Ollama model. |
| `input_type` | `COMBO` (`text`, `image`) | The type of input to send. `text` for text-only prompts, and `image` to include images. |
| `ollama_model` | `COMBO` | A list of available Ollama models on your local instance. |
| `keep_alive` | `INT` | The duration (in minutes) that the Ollama model should remain loaded in memory after the request is complete. |
| `saved_sys_prompt` | `COMBO` | A dropdown list of saved system prompts from the `.txt` files in the `prompts` directory. This is used as the system prompt by default. |
| `use_sys_prompt_below` | `BOOLEAN` | If checked (`True`), the `system_prompt` text box below will be used instead of the dropdown selection. If unchecked (`False`), the `saved_sys_prompt` dropdown is used. |
| `system_prompt` | `STRING` | A multiline text box for a custom, one-off system prompt. This is only active when `use_sys_prompt_below` is checked. |
| `image1` - `image5` | `IMAGE` (Optional) | Up to five optional image inputs for multimodal models. |
| Name | Type | Description |
| ---------------------- | --------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `prompt` | `STRING` | The main text prompt to send to the Ollama model. |
| `ollama\_model` | `COMBO` | A list of available Ollama models on your local instance. |
| `keep\_alive` | `INT` | The duration (in minutes) that the Ollama model should remain loaded in memory after the request is complete. |
| `saved\_sys\_prompt` | `COMBO` | A dropdown list of saved system prompts from the `.txt` files in the `prompts` directory. This is used as the system prompt by default. |
| `use\_sys\_prompt\_below` | `BOOLEAN` | If checked (`True`), the `system\_prompt` text box below will be used instead of the dropdown selection. If unchecked (`False`), the `saved\_sys\_prompt` dropdown is used. |
| `system\_prompt` | `STRING` | A multiline text box for a custom, one-off system prompt. This is only active when `use\_sys\_prompt\_below` is checked. |
| `image1` - `image5` | `IMAGE` | Up to five optional image inputs for multimodal models. The node will automatically detect and process any connected images. |
### Outputs
@@ -58,6 +59,23 @@ The `BasicOllama` node can be found under the `Ollama` category in the ComfyUI m
| ------ | -------- | ----------------------------------------- |
| `text` | `STRING` | The text-based response from the Ollama model. |
## ✍️ Adding Custom System Prompts
You can easily add your own reusable system prompts to the `saved\_sys\_prompt` dropdown menu.
1. Navigate to the `ComfyUI-BasicOllama/prompts` directory.
2. Create a new text file (e.g., `my\_prompt.txt`).
3. Write your system prompt inside this file. For example, if you want a system prompt for generating JSON, the content of the file could be:
  ```
You are a helpful assistant that only responds with valid, well-formatted JSON.
```
4. Save the file.
5. Refresh your ComfyUI browser window.
The name of your file (without the `.txt` extension) will now appear as an option in the `saved\_sys\_prompt` dropdown. In the example above, you would see `my\_prompt` in the list.
## ⚙️ Configuration
By default, the `BasicOllama` node will attempt to connect to your Ollama instance at `http://localhost:11434`.
@@ -66,11 +84,12 @@ If your Ollama instance is running on a different URL/port, you can change it by
```json
{
"OLLAMA_URL": "http://your-ollama-url:11434"
"OLLAMA\_URL": "http://your-ollama-url:11434"
}
```
## 🙏 Attribution
A special thank you to [@al-swaiti](https://github.com/al-swaiti) for creating the original [ComfyUI-OllamaGemini](https://github.com/al-swaiti/ComfyUI-OllamaGemini) which served as the foundation for this.
A special thank you to [@al-swaiti](https://github.com/al-swaiti) for creating the original [ComfyUI-OllamaGemini](https://github.com/al-swaiti/ComfyUI-OllamaGemini) whose Ollama node served as the foundation and inspiration for this.
This project is licensed under the [MIT License](LICENSE).